CN110988877B - Satellite-borne high-resolution SAR high squint Doppler deconvolution method - Google Patents
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Abstract
The invention discloses a satellite-borne high-resolution SAR large squint Doppler decoiling method which comprises the steps of firstly, carrying out deformation processing on satellite-borne high-resolution SAR large squint mode two-dimensional spectrum data by using cyclic shift operation; then carrying out support domain expansion processing on the deformed data; and finally, performing two-dimensional spectrum recovery processing on the data after the support domain expansion by using cyclic shift operation to realize the deconvolution of the Doppler domain of the two-dimensional spectrum data. The invention realizes the removal of the two-dimensional spectrum Doppler domain winding phenomenon, and solves the problems of energy leakage and a large number of false target conditions caused by Doppler domain spectrum winding. The decoiling method realizes frequency spectrum processing by using cyclic shift operation, avoids calculating echo data, and has very high processing efficiency and application efficiency.
Description
Technical Field
The invention belongs to the field of signal processing, and relates to a satellite-borne high-resolution SAR large squint Doppler deconvolution method.
Background
In order to meet the flexible observation requirement of the high-resolution SAR load and realize the application efficiency of target multi-angle information fusion and multi-region rapid observation, the high-resolution satellite-borne SAR needs to have the working capacity under a large squint angle. The existing satellite-borne SAR works under the condition of front side view, and the flexibility is limited. Under the promotion of application requirements, a high-resolution large squint working mode is a development direction of a next generation of satellite-borne SAR. However, in the wide-band large squint observation mode, different from the traditional front squint observation, the target signal will show some new characteristics, wherein the most significant signal characteristic change is that the signal spectrum will have a wraparound phenomenon in the doppler domain. The existing spaceborne SAR signal processing algorithm is mainly designed based on a front-side view observation mode, and because the signal in the spaceborne SAR front-side view mode does not have the spectrum Doppler domain winding phenomenon, the existing spaceborne SAR algorithm does not consider the Doppler winding problem, does not have the capability of processing a large squint observation mode, and lacks an effective means for removing the Doppler winding phenomenon. If the spectral Doppler warping removal process is not carried out, serious energy leakage and a large number of false targets occur in a large squint observation mode, and the image quality and the target interpretation are seriously influenced.
Disclosure of Invention
The technical problem solved by the invention is as follows: the method overcomes the defects of the prior art, provides the spaceborne high-resolution SAR large squint Doppler unwrapping method, achieves removal of the wrapping phenomenon of the two-dimensional spectrum Doppler domain, solves the problems of energy leakage and a large number of false targets caused by Doppler domain spectrum wrapping, avoids computation of echo data, and has very high processing efficiency and application efficiency.
The technical scheme of the invention is as follows:
a satellite-borne high-resolution SAR high squint Doppler deconvolution method comprises the following steps:
(1) carrying out deformation processing on the two-dimensional spectrum data of the satellite-borne high-resolution SAR large squint mode;
(2) carrying out support domain expansion processing on the deformed data;
(3) and performing two-dimensional spectrum recovery processing on the data after the support domain expansion.
The method comprises the steps of carrying out deformation processing on satellite-borne high-resolution SAR large squint mode two-dimensional spectrum data, calculating deformation cyclic shift points corresponding to data columns at each range-direction frequency point position and carrying out cyclic shift processing on the data columns at each range-direction frequency point position along a Doppler dimension.
The method for calculating the number of deformation cyclic shift points comprises the following steps:
wherein Ls represents the number of deformation cyclic shift points, F _ dat _ s represents the data after shift, c represents the speed of light, floor [ 2 ]]Represents a rounding-down operation, V represents a satellite effective speed, theta represents a squint angle, PRF represents a system pulse repetition frequency, M is the number of received pulse echoes corresponding to one scene data, fc is a SAR system carrier frequency, and F _ dat (F)r,fa) Two-dimensional spectral data corresponding to a scene of SAR echoes, fr distance direction frequency, fa doppler frequency,
a list of two-dimensional spectrum data with a distance fr _ n to the frequency point is shown.
The processing mode of circularly shifting the data columns of the positions of the distances to the frequency points along the Doppler dimension is as follows:
for a column of two-dimensional spectrum data with distance to frequency point fr _ n
A cyclic shift process is performed along the doppler dimension,
wherein, F _ dat _ s represents data after shifting, shft () represents cyclic shift operation, Ls represents deformation cyclic shift point number, and shft () carries out positive shift when the number is positive and carries out negative shift when the number is negative.
The support domain expansion processing of the deformed data comprises two steps of calculating the minimum expansion point number at one end of the data and respectively carrying out zero filling expansion not less than the minimum expansion point number at the head end and the tail end of the deformed two-dimensional frequency spectrum data.
The method for calculating the minimum expansion point number at one end of the data comprises the following steps:
wherein, K represents the minimum expansion point number at one end of the data, and Fs is AD sampling frequency.
And the support domain expansion is realized by respectively performing zero padding expansion on the head end and the tail end of the deformed two-dimensional frequency spectrum data, wherein the zero padding expansion is not less than 0 value of K minimum expansion points. Assuming that M is the number of received pulse echoes corresponding to one scene of data, and the number of zero padding at one end is K _ M, the number of data points of the doppler dimension after zero padding is changed from M to M +2 × K _ M.
The two-dimensional spectrum recovery processing of the data after the support domain expansion comprises two steps of calculating recovery cyclic shift points corresponding to data columns at each distance-direction frequency point position and performing cyclic shift processing on the data columns at each distance-direction frequency point position along a Doppler dimension.
The calculation method for recovering the cyclic shift point number comprises the following steps:
where P represents the number of cyclic shift points in the two-dimensional spectrum restoration process.
Let F _ dat _ e denote the data after the support domain expansion. Two-dimensional spectrum data after a row of distance directional frequency points fr _ n is expanded
And carrying out cyclic shift processing along the Doppler dimension to realize two-dimensional spectrum recovery. The cyclic shift processing mode is as follows:
wherein, F _ dat _ r represents the two-dimensional spectrum restored data.
Compared with the prior art, the invention has the advantages that:
(1) compared with the prior art, the method has the advantages that the high-resolution large squint SAR signal spectrum Doppler winding phenomenon is removed by performing cyclic shift deformation, support domain expansion and two-dimensional spectrum cyclic shift recovery on the two-dimensional spectrum, so that the problems of energy leakage and false target caused by large squint signal Doppler winding are solved;
(2) the invention provides a signal unwrapping processing step flow aiming at a signal spectrum. The process is a universal signal processing process, can be used as a preprocessing step to be matched with various front-side-view imaging algorithms, can be conveniently realized in various processors such as a DSP (digital signal processor), an FPGA (field programmable gate array), an ARM (advanced RISC machine) and the like, and has good universality.
(3) The method can simply and quickly realize the decoiling processing under the broadband high-resolution SAR squint, wherein the processing such as interpolation, signal filtering calculation and the like is not involved, the calculation of echo data is avoided, the processing can be realized only by signal numerical value translation and data expansion, the processing scheme is simple and easy to implement, and the method has very high processing efficiency and application efficiency.
Drawings
FIG. 1 is a data processing flow diagram of the present invention;
FIG. 2 is a schematic diagram of cyclic shift;
FIG. 3 is a two-dimensional spectrogram of a downward-warped coil in a greatly oblique view;
FIG. 4 is a two-dimensional spectrogram after a spectral warping process;
FIG. 5 is a two-dimensional spectrogram after a support domain expansion process;
FIG. 6 is a two-dimensional spectrogram after a spectral recovery warping process;
FIG. 7 is a graph of imaging results when the wrap is not removed in a steep oblique view;
fig. 8 is a graph of imaging results after removing the wrap in a steep oblique view.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention provides a method for removing a Doppler frequency spectrum winding phenomenon of a signal in a satellite-borne high-resolution SAR large squint observation mode, which solves the influence caused by the Doppler frequency spectrum winding phenomenon of the signal in the satellite-borne broadband large squint observation mode. As shown in fig. 1, the method mainly includes three parts, namely two-dimensional spectrum deformation, support domain expansion and two-dimensional spectrum restoration, and specifically includes the following steps:
step one, deformation processing is carried out on satellite-borne high-resolution SAR large squint mode two-dimensional frequency spectrum data
For a broadband SAR system, when the system is in a large squint observation mode, broadband deformation distortion occurs in a two-dimensional support domain of a frequency spectrum, and the band edge exceeds Doppler sampling bandwidth coverage in a Doppler dimension, so that a two-dimensional frequency spectrum Doppler winding phenomenon is generated, and image quality is reduced.
A two-dimensional spectrogram of a support domain under a broadband spaceborne SAR squint is shown in fig. 3. It can be seen from the figure that under the condition that the frequency spectrum is subjected to broadband deformation distortion, the two-dimensional frequency spectrum exceeds the sampling frequency band, the frequency spectrum at the upper left corner is wound to the upper right corner position, the frequency spectrum at the lower right corner is wound to the lower left corner position, and the frequency spectrum is seriously fractured.
For the phenomenon, firstly, two-dimensional spectrum data deformation processing is carried out, and the deformed spectrum Doppler support domain is within the Doppler sampling bandwidth.
For a digital signal sampling SAR system, let V denote the satellite effective speed, theta denote the squint angle, PRF denote the system pulse repetition frequency, M is the number of received echo pulses corresponding to a scene data, Fs is the AD sampling frequency, N is the number of AD sampling points corresponding to an echo pulse, fcFor SAR system carrier frequency, F _ dat (F)r,fa) As a single SAR echoCorresponding two-dimensional spectral data, frRepresenting the range frequency, faIndicating the doppler frequency.
The method comprises the steps of carrying out deformation processing on satellite-borne high-resolution SAR large squint mode two-dimensional spectrum data, calculating deformation cyclic shift points corresponding to data columns at each range-direction frequency point position and carrying out cyclic shift processing on the data columns at each range-direction frequency point position along a Doppler dimension.
The specific two-dimensional spectrum data deformation method is as follows:
for a column of two-dimensional spectrum data with distance to frequency point fr _ n
And (3) performing cyclic shift processing along the Doppler dimension, and calculating the number Ls of deformed cyclic shift points by using the following formula:
the method for performing deformation processing on the data column by using the deformation cyclic shift point number is as follows:
wherein, F _ dat _ s represents shifted data, c represents light speed, ft () represents cyclic shift operation, floor [ ] represents rounding-down operation, Ls represents cyclic shift point number, and ft () performs positive shift when the number is positive and performs negative shift when the number is negative.
Fig. 2 shows a deformation process of a data column of the spectrum data. The shaded portion of the two-dimensional spectrum in figure 2(a) represents a column of data distributed along the doppler dimension. Fig. 2(b) shows schematic diagrams of the data sequence before and after movement, taking Ls-2 and M-7 as examples.
Fig. 4 shows a spectrum shape obtained by performing cyclic shift processing on all data columns of two-dimensional data to realize spectrum deformation.
Step two, carrying out support domain expansion processing on the deformed data
And (4) carrying out zero filling processing at two ends aiming at the data after the two-dimensional frequency spectrum deformation to realize the support domain expansion. Wherein, the zero padding number of one end is not less than the following number:
wherein K represents the lower limit of the number of zero padding at one end. During processing, 0 values which are not less than K numbers are respectively added at the head end and the tail end of the Doppler dimension of the data, so that data expansion is realized. Assuming that the number of zero padding at the front end is K _ M1 and the number of zero padding at the back end is K _ M2, the number of data points in the Doppler dimension after zero padding will be changed from M to M + K _ M1+ K _ M2.
The two-dimensional spectrogram after the support domain expansion is shown in fig. 5.
Step three, performing two-dimensional frequency spectrum recovery processing on the data after the support domain expansion to realize the de-winding of the Doppler domain of the two-dimensional frequency spectrum data
The two-dimensional spectrum recovery processing of the data after the support domain expansion comprises two steps of calculating recovery cyclic shift points corresponding to data columns at each distance-direction frequency point position and performing cyclic shift processing on the data columns at each distance-direction frequency point position along a Doppler dimension.
Specifically, let F _ dat _ e denote data after the support domain expansion. Similarly, for two-dimensional spectrum data after distance expansion to a column of support domains with frequency points fr _ n
And carrying out cyclic shift processing along the Doppler dimension to realize two-dimensional spectrum recovery. The number of recovery cyclic shift points Lr is as follows:
the data column is deformed by the number of recovery cyclic shift points as follows:
wherein,
represents data after recovery of two-dimensional spectrum data after distance extension to a column of support domain with frequency point fr _ n, and shft () represents a cyclic shift operation.
After the two-dimensional spectrum recovery processing, a broadband large squint two-dimensional spectrogram for realizing the two-dimensional spectrum unwrapping is shown in fig. 6. As can be seen from the figure, the shape of the processed spectrum is effectively recovered, and compared with the spectrum which is subjected to coiling in the figure 3, the spectrum which is subjected to uncoiling is continuously distributed, and coiling and fracture phenomena are effectively removed.
The method can be used as a preprocessing universality algorithm and can be integrated with the existing imaging algorithm on the premise of not modifying the imaging algorithm. For the large squint observation data without the two-dimensional spectrum unwrapping process, the imaging process result is shown in fig. 7, and it can be seen from the figure that the target with energy leakage and fuzzy defocusing appears on both sides of the target. After the unwrapping preprocessing is performed by the method, imaging focusing processing is performed on unwrapped data by using the existing imaging algorithm, and an obtained imaging result is shown in fig. 8. Comparing fig. 7, it can be seen that the energy leakage interference on both sides of the target disappears, which indicates that the method effectively implements spectrum winding removal and greatly improves the imaging result.
Aiming at the SAR satellite high-resolution large squint observation mode, the method realizes the removal of the two-dimensional spectrum Doppler domain winding phenomenon through the treatments of two-dimensional spectrum rapid deformation, support domain expansion, two-dimensional spectrum rapid recovery and the like, and solves the problems of energy leakage and a large number of false target conditions caused by Doppler domain spectrum winding. The decoiling method realizes frequency spectrum processing by using cyclic shift operation, avoids calculating echo data, and has very high processing efficiency and application efficiency.
The invention is not described in detail and is within the knowledge of a person skilled in the art.
Claims (7)
1. A satellite-borne high-resolution SAR high squint Doppler deconvolution method is characterized by comprising the following steps:
the method comprises the following steps: carrying out deformation processing on the two-dimensional spectrum data of the satellite-borne high-resolution SAR large squint mode;
dividing the two-dimensional frequency spectrum data into data columns at each distance direction frequency point position, calculating the deformation cyclic shift point number corresponding to each data column, and performing deformation processing on each data column by using the deformation cyclic shift point number;
step two: carrying out support domain expansion processing on the deformed data;
step three: performing two-dimensional spectrum recovery processing on the data after the support domain expansion to realize the unwinding of the Doppler domain of the two-dimensional spectrum data;
the method for carrying out two-dimensional spectrum recovery processing on the data after the support domain expansion comprises the following steps: dividing the data after the support domain expansion into data columns at the positions of the frequency points in each distance direction, calculating the number of recovery cyclic shift points corresponding to each data column, and performing deformation processing on each data column by using the number of the recovery cyclic shift points.
2. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 1, characterized in that: for a column of two-dimensional spectrum data with distance to frequency point fr _ n
Calculating the number Ls of deformation cyclic shift points by using the following formula:
wherein c represents a light velocity, floor 2]Representing a rounding-down operation, V representing the satellite effective velocity, theta representing the squint angle, PRF representing the system pulse repetition frequency, fcFor SAR system carrier frequency, F _ dat (F)r，fa) Representing two-dimensional spectral data corresponding to a scene of SAR echoes, frRepresenting the range frequency, faThe Doppler frequency is shown, and M is the number of received pulse echoes corresponding to one scene of data.
3. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 2, characterized in that: the method for performing deformation processing on the data column by using the deformation cyclic shift point number is as follows:
wherein,
represents data shifted from a row of two-dimensional spectrum data with a frequency point fr _ n, shft () represents a cyclic shift operation, and shft () shifts positively when Ls is a positive number and shifts negatively when Ls is a negative number.
4. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 1, characterized in that: in the second step, the method for performing support domain expansion processing on the deformed data comprises the following steps:
(2.1) calculating the minimum expansion point number at one end of the data;
and (2.2) respectively performing zero filling expansion not less than the minimum expansion point number at the head end and the tail end of the two-dimensional frequency spectrum data subjected to the deformation processing in the step one, and realizing the expansion processing of the data support domain.
5. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 4, characterized in that: in the step (2.1), the minimum expansion point number K at one end of the data is calculated by using the following formula:
wherein Fs is AD sampling frequency, c is light speed, floor [ ] is rounding-down operation, V is satellite effective speed, θ is squint angle, PRF is system pulse repetition frequency, and M is the number of received pulse echoes corresponding to a scene data.
6. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 1, characterized in that: two-dimensional spectrum data after expanding a column of support domains with distance to frequency point fr _ n
The number of recovery cyclic shift points Lr is calculated using the following formula:
wherein c represents a light velocity, floor 2]Representing a rounding-down operation, V representing the satellite effective velocity, theta representing the squint angle, PRF representing the system pulse repetition frequency, fcFor SAR system carrier frequency, frRepresenting the range frequency, faThe Doppler frequency is shown, and M is the number of received pulse echoes corresponding to one scene of data.
7. The spaceborne high-resolution SAR high squint Doppler deconvolution method according to claim 6, characterized in that: the data column is deformed by the recovery cyclic shift point number as follows:
wherein,
representing two dimensions after extension of the distance to a column of support fields with frequency points fr _ nFor the spectrum data recovered data, shft () represents a cyclic shift operation.
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